1. Field of the Invention
The invention generally relates to the field of enterprise resource planning, particularly to the assessment of cost of manufactured goods, and, more specifically, to a technique of increasing the accuracy of costing manufactured goods.
2. Description of the Related Art
Enterprise resource planning systems are used for unified integration of all data and processes of an organization. Typically, an enterprise resource planning system uses multiple components of computer software and hardware to achieve the integration. One important software module is a unified database to store data for the various system modules. Depending on the size of the system, data modules and system modules may be both physically and logically distributed. Physical distribution means that the components are spread over different hardware (e.g. servers) whereas logical distribution describes a functional separation of the modules which may be implemented on the same hardware platform.
Enterprise resource planning systems have conventionally been implemented primarily in the manufacturing environment, but today they are used in a much broader scope, i.e. covering all basic functions of an organization, regardless of the organization's business character. Generally, the benefit of an enterprise resource planning system is to replace two or more independent applications, eliminating the need for external interfaces previously required between systems. Additional benefits range from standardization and lower maintenance of fewer systems (e.g., one system instead of two or more systems) to allowing easier and/or greater reporting capabilities (since, for example, all data is typically kept in one database with only one well defined interface).
The term “costing” describes the process of identifying the costs of the business and of breaking them down and relating them to the various activities of the organization. In order to determine the factory costs for a given product, typically cost estimates are developed at all stages of a product development and product production cycle based on a plurality of scenarios, for example, describing potential future variations of schedule, production site, technology, suppliers, subcontractors, tariffs, prices etc. In other words, costing is a process which requires analysis, simulation, and optimization of future production costs.
The analysis process covers identifying all raw materials, preliminary products and production passes necessary to manufacture the final finished product. In the simulation process, the influence of technical alternatives, increasing product and project complexity and innovation management is examined, including the evaluation of economic alternatives such as the trade-off between make or buy, the production site selection, the supplier selection and the target date for the start of the production. Finally, in the optimization process the processing of data obtained in the simulation phase is structured in a beneficial manner, usually to minimize the overall cost.
Though calculation of these processes could be performed by computer programs (such as spreadsheet calculators) or, even in a person's memory (e.g., in cases of low complexity), it is evident that in order to increase the calculation quality, the costing of complex products requires structuring, standardization, versioning, automated quality testing, audit proof archiving and incorporation of different calculations.
Furthermore, the costing process is subject to market trends such as cost pressure and risk dislocation requiring a design to cost or target cost calculation or defined usage of standardized parts. Thus, if a high proliferation of options is important, costing includes variant management for simulation of technical alternatives such as product structures, production and processes. If, however, an increased outsourcing is desired, variant management for simulating economical alternatives with respect to the selection of suppliers and determination of the right place and time is required.
Global determination of cost process analysis may include budgeted product and project controlling costs and specific investment management considerations. Other considerations in cost process analysis, such as increased differentiation, can require innovation management and a benchmark with function costs analysis. In summary, costing captures various trends by means of methodical expertise resulting in a combination of technical and economical perspectives by identification of the specific cost drivers, the defined usage of standardized parts and a lifetime simulation.
As a module of an enterprise resource planning system, costing is generally highly communicative with other modules or the user of the system and provides cost transparency for a flexible reporting system. For a better understanding of this concept, the following example is provided to demonstrate an application of the aforementioned concept:
A customer requests a quotation for a certain product from a supplier expecting a pricing of the quotation based on the requirements stated either in the quotation or by reference to known industry standards. The supplier starts with a decision of whether or not the product meets the given requirements. If this decision is positive, the supplier either imports an existing calculation of a bill of materials or creates a new product structure. Now the supplier initiates an internal optimization process by iteratively adapting the calculation towards the cost target. This phase includes the identification of cost reduction potential, costed evaluation of technical alternatives, suppliers and site selection. Ideally, the supplier meets the cost target and starts the production after signing the contract with the customer. One should note that depending on the type of industry, the unilateral calculation towards the cost target could also include the cost consideration of the entire value chain, integrating suppliers and customers, for example, by aiming at stronger negotiation positions when purchasing raw materials or by balancing product cost versus cost in use.
Thus, a so-called “ABC analysis” has been provided as a common practice for grouping all cost related items into three categories: namely, A for cost relevant items, B for less cost relevant items and C for items with only minor cost relevance.
While optimizing cost relevant parameters in order to meet a cost target, it may be desirable to make preliminary production related decisions. Such decisions can be related to various production scenarios. Furthermore, one set of production scenarios may be unique from other kinds of production scenarios depending upon specific situations. For example, it would be desirable to make a determination to postpone the start of production, e.g., when a drastic decrease in a purchase price for product parts is expected in the near future.
In another example, it is generally known that production costs can vary considerably among different production sites. Hence, it would be desirable to be able to calculate these differences and utilize them for the compilation of best and worst case scenarios. In another example, an accurate cost analysis is desirable for the evaluation of alternatives in production technology. In yet another example, an accurate cost analysis is desirable for selecting a choice of suppliers for purchasing parts and the availability of block pricing and rebates.
Thus, a need exists to provide a cost analysis simulation capable of automatically addressing cost relevant parameters and weighing all these parameters against each other to provide/suggest an optimal set of choices between alternatives for various situations including, for example, those outlined above.